Instructions to use ProbeX/Model-J__ResNet__model_idx_0878 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__ResNet__model_idx_0878 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__ResNet__model_idx_0878") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0878") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0878") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e392edcddfd2aa35a92ddf1749fd8dff622fab1506df291052ae570c97882f19
- Size of remote file:
- 5.37 kB
- SHA256:
- 13515b213aebc9ecc86fae4b7036ab166e42c0363407ce7cb0ebcccba233f32b
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